Russian attacks on Ukraine killed one person and wounded seven others in the Dnipropetrovsk region, according to the country's emergency service. High-rise buildings, homes, shops and cafes were also damaged. Another person was wounded by shelling in the Zaporizhia region, the service said, with a blast also destroying three residential buildings and 12 homes. In the Donetsk region, at least two people were killed, and five more were wounded, in 13 separate Russian attacks across multiple districts, according to Governor Vadym Filashkin. A total of 172 people, including 35 children, were evacuated from the front line, Filashkin said.

SoftBank Group is in discussions to invest as much as $30 billion more in OpenAI, a sharp increase in commitment that reflects founder Masayoshi Son's ambitions to play a central role in developing artificial intelligence. The Japanese company, already one of the ChatGPT-maker's biggest backers, is in deliberations to commit more capital toward the fast-growing startup, people familiar with the matter said. The maximum amount SoftBank is considering is $30 billion, one of the people said, asking to remain anonymous to discuss private talks. They cautioned that the discussions are fluid and the amount of funding could change. SoftBank's shares rose 5.8% in Tokyo on Wednesday. Son has been unwinding positions to increase its stake in OpenAI and ready capital for sweeping investments aimed at injecting AI in all devices.

Virtually defenseless: Moscow's attacks in Ukraine put fear into neighboring Moldova Palanca, Moldova - The village of Palanca felt the full horror of the war in neighboring Ukraine one December day. A mother was killed and her three children wounded by a Russian drone as they drove over the border bridge across the river Dniester into this previously quiet corner of southeastern Moldova, Ukrainian officials said. We are right across from there, and it terrified us, villager Maria Morari, 62, said of the two days of attacks on the crossing. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right. With your current subscription plan you can comment on stories.

Topological methods have the potential of exploring data clouds without making assumptions on their the structure. Here we propose a hierarchical topological clustering algorithm that can be implemented with any distance choice. The persistence of outliers and clusters of arbitrary shape is inferred from the resulting hierarchy. We demonstrate the potential of the algorithm on selected datasets in which outliers play relevant roles, consisting of images, medical and economic data. These methods can provide meaningful clusters in situations in which other techniques fail to do so.

Russia has intensified its strikes on the southern Ukrainian region of Odesa, causing widespread power cuts and threatening the region's maritime infrastructure. Ukrainian Deputy Prime Minister Oleksiy Kuleba said Moscow was carrying out systematic attacks on the region. Last week, he warned that the focus of the war may have shifted towards Odesa. President Volodymyr Zelensky said the repeated attacks were an attempt by Moscow to block Ukraine's access to maritime logistics. Earlier in December, Russian President Vladimir Putin threatened to sever Ukraine's access to the sea as retaliation for drone attacks on tankers of Russia's shadow fleet in the Black Sea.

We study distributionally robust Markov games (DR-MGs) with the average-reward criterion, a framework for multi-agent decision-making under uncertainty over extended horizons. In average reward DR-MGs, agents aim to maximize their worst-case infinite-horizon average reward, to ensure satisfactory performance under environment uncertainties and opponent actions. We first establish a connection between the best-response policies and the optimal policies for the induced single-agent problems. Under a standard irreducible assumption, we derive a correspondence between the optimal policies and the solutions of the robust Bellman equation, and derive the existence of stationary Nash Equilibrium (NE) based on these results. We further study DR-MGs under the weakly communicating setting, where we construct a set-valued map and show its value is a subset of the best-response policies, convex and upper hemi-continuous, and derive the existence of NE. We then explore algorithmic solutions, by first proposing a Robust Nash-Iteration algorithm and providing convergence guarantees under some additional assumptions and a NE computing oracle. We further develop a temporal-difference based algorithm for DR-MGs, and provide convergence guarantees without any additional oracle or assumptions. Finally, we connect average-reward robust NE to discounted ones, showing that the average reward robust NE can be approximated by the discounted ones under a large discount factor. Our studies provide a comprehensive theoretical and algorithmic foundation for decision-making in complex, uncertain, and long-running multi-player environments.

As Large Language Models (LLMs) become increasingly integrated into everyday life and information ecosystems, concerns about their implicit biases continue to persist. While prior work has primarily examined socio-demographic and left--right political dimensions, little attention has been paid to how LLMs align with broader geopolitical value systems, particularly the democracy--authoritarianism spectrum. In this paper, we propose a novel methodology to assess such alignment, combining (1) the F-scale, a psychometric tool for measuring authoritarian tendencies, (2) FavScore, a newly introduced metric for evaluating model favorability toward world leaders, and (3) role-model probing to assess which figures are cited as general role-models by LLMs. We find that LLMs generally favor democratic values and leaders, but exhibit increased favorability toward authoritarian figures when prompted in Mandarin. Further, models are found to often cite authoritarian figures as role models, even outside explicit political contexts. These results shed light on ways LLMs may reflect and potentially reinforce global political ideologies, highlighting the importance of evaluating bias beyond conventional socio-political axes. Our code is available at: https://github.com/irenestrauss/Democratic-Authoritarian-Bias-LLMs.

What is in the 28-point US plan for Ukraine? 'Ukraine is running out of men, money and time' Can the US get all sides to end the war? Why is Europe opposing Trump's peace plan? Here's where things stand on Sunday, November 30. A Russian drone attack killed one person and wounded 11, including a child, on the outskirts of the Ukrainian capital, Kyiv, regional Governor Mykola Kalashnyk said on Sunday.

For example, in the Pandemic Response Challenge experiment, the context consisted of data about the geographic region for which the predictions were made, e.g., historical data of COVID-19 cases and intervention policies; actions were future schedules of intervention policies for the region; and outcomes were predicted future cases of COVID-19 along with the stringency